Industrial Clusters Research Articles

IMPLEMENTATION OF THE NIGERIAN AUTOMOTIVE INDUSTRY DEVELOPMENT PLAN, 2014 ON THE DEVELOPMENT OF AUTOMOTIVE CLUSTER PARKS

The study evaluates the implementation of the Nigerian Automotive Industry Development Plan (NAIDP), 2014 on the development of automotive cluster parks by the National Automotive Design and Development Council (NADDC). The study sought specifically to find out the extent NADDC has facilitated the establishment of industrial automotive cluster parks in various states in Nigeria. The study adopted a descriptive survey research design. Primary and secondary data were employed, while frequency and percentage analyses were performed. The study found that the extent National Automotive Design Development Council has facilitated the establishment of industrial automotive cluster parks in the selected zones in Nigeria was low, when judged against the implementation checklist. It was therefore concluded that the implementation of NAIDP,2014 on the development of automotive cluster parks by NADDC was not effective. Based on the findings, it was recommended that NAIDP, 2014 should be reviewed with new and feasible timelines. Furthermore, the federal government should give incentives to private investors to encourage them to develop cluster parks in Nigeria.

Digital Economy and Sustainable Development in China: From the Perspective of High-Quality Development of Manufacturing

This study investigates the role of the digital economy (DE) in advancing the high-quality development of manufacturing in China, with a particular focus on the moderating effects of manufacturing agglomeration and digital literacy. Using provincial panel data from 2013 to 2023, we find that the digital economy significantly enhances manufacturing development across three key dimensions: green transformation, innovation, and high-end industrial upgrading. Manufacturing agglomeration strengthens this effect, especially in the Eastern and Western regions, by facilitating digital spillovers and leveraging digital infrastructure. However, in the Central region, the impact of agglomeration is weaker, hindered by fragmented industrial clusters and underdeveloped digital infrastructure. The study also highlights significant regional differences in the moderating effect of digital literacy. In the Eastern region, digital literacy negatively moderates the relationship between DE and manufacturing development due to skill mismatches, while in the Western region, localized concentrations of digital skills have a positive but geographically constrained impact. Temporal analysis reveals a shift in the moderating role of digital literacy, with its negative effect becoming more pronounced after 2018, suggesting a growing need for targeted skill development policies. These findings underscore the importance of regionally tailored strategies to promote digital manufacturing integration, with a focus on sustainable development through digital transformation and green manufacturing practices.

A contextual analysis of clusters in Morocco : What lessons for an integrated territorial policy and more competitive SMEs ?

The territory has become an area of research that is increasingly interesting to the scientific community due to its crucial role in the sustainable and efficient development of national businesses. As a result, a network of competitive ecosystems has been steadily developing since the launch of the "Competitive Morocco" plan in 1995, leading to various forms of inter-organizational agglomeration such as integrated industrial platforms, technopoles, and clusters. However, the Moroccan context lacks qualitative and quantitative studies to fully understand and grasp the variety, multiplicity, and specificities of the existing ecosystem forms. To address this gap, we conducted an exploratory study using an interpretativist approach, focusing on a specific form of grouping known as clusters. The aim was to understand the pace of change in this territorial mechanism, analyze its intervention strategies, and assess its geographical and sectoral distribution across the country. Our work resulted in an analytical map based on a non-probabilistic sample of 17 clusters, enabling us to capture the state of cluster evolution by geographical region, sector, intervention strategies, governance mode, and financing. The results from this exploratory study will be utilized in a second confirmatory study to measure the impact of territorial mechanisms on business competitiveness.

MEASUREMENT OF ABSORPTIVE CAPACITY IMPLICATIONS IN SMALL AND MEDIUM INDUSTRIES

The post-covid-19 era is a momentum for all types of business models to immediately reach their highest performance after dropping drastically due to the economic recession. The manufacturing industry is one type of business model that is under enormous pressure during Covid-19 and is required to immediately return to normal. Small and medium industries as a class of manufacturing industry are unique in their ability to recover quickly, apart from the fact that their industrial model is quite small, many of these small and medium industries also form industrial clusters. In the current era of knowledge-based economy, one theory provides an illustration that if a business organization wants to quickly achieve business performance, it needs to master the necessary knowledge. This concept is called absorptive capacity which explains how a business organization acquires knowledge and implements it to gain competitive advantage. This research tries to present a factor analysis on the theoretical concept of absorptive capacity (with the dimensions of acquisition, assimilation, transformation, and exploitation) in a small and medium industrial cluster. There were 127 respondents from the small and medium Logam industrial cluster in Ngingas Village, Waru Distric, Sidoarjo - Indonesia. This research reveals that in the small and medium Logam industrial cluster in Ngingas Waru Sidoarjo - Indonesia, the acquisition factor is the dominant factor in the process of mastering knowledge that comes from outside the organization and the assimilation factor is the least dominant factor in the process of mastering knowledge.

The role of industry 4.0 and open innovation practices in the renewal path of an industrial cluster

ABSTRACT This paper aims to analyze the role of open innovation practices supporting organizations and local inter-organizational interactions in the digital transformation of an industrial cluster for the adoption of Industry 4.0 technologies. To do so, we conducted qualitative research based on a case study methodology using primary and secondary data to analyze the case of the Automotive Metal-Mechanic Cluster (AMMC) of the Serra Gaúcha, in the south of Brazil. The results highlight different reactions to the transformations imposed by Industry 4.0 on the various actors of the AMMC. Large companies are ahead in the movement toward digitalization by collaborating with other companies and adapting their own culture, technologies, and new competencies to the Industry 4.0 paradigm. Small and medium-sized companies (SMEs) react differently by using local support organizations (the Helix Institute) to adapt, presenting weaker network connections and more restricted technological capabilities.

Drivers of artificial intelligence innovation in manufacturing clusters: insights from cellular automata simulations

With the rapid development of the global economy and artificial intelligence (AI) technologies, AI-driven innovation has become a key driver of economic growth in manufacturing clusters. This study investigates the main drivers of AI innovation in manufacturing clusters through the lens of evolutionary economic geography theory. Three primary driving factors are identified: cluster resources, cluster networks, and cluster environments. An evolutionary model based on Cellular Automata (CA) is developed to quantitatively analyze their influence, followed by simulation experiments. The results show a positive correlation between these factors and the evolution of AI innovation within industrial clusters. Further case studies of AI-enabled manufacturing clusters, including Zhongguancun, Shenzhen, and Bangalore, substantiate these findings. The study highlights the critical role of resource endowments, AI-driven inter-firm collaboration, and supportive policy frameworks in fostering AI innovation. The findings provide a deeper understanding of clustered innovation ecosystems and the theoretical foundations of collective learning and competitive advantage in the AI era. This research also has broad implications, particularly for interdisciplinary studies in digital humanities, complex network analysis, and the socioeconomic impact of AI-driven technological transformation.

Expected health risk out of black carbon and particulate matter in the indoor environment of an industrial cluster of chandigarh in India

The global increase in industrialization and its attendant exponential air pollution has posed a significant hazard to the indoor pollution levels of cities and the associated health risks. This study evaluated the health effects of air pollutants discovered inside the bottling industries in Chandigarh cluster in India. PM10, PM2.5, PM1, and black carbon concentrations in the post-monsoon season were monitored, and associated health implications and lung disease were estimated. A positive correlation is established between PM in indoor and outdoor environments. Maximum concentrations for PM10, PM2.5, and PM1 were recorded as 276.8 µg/m3, 97.7 µg/m3 and 66.5 µg/m3 (for indoor) respectively, which are approximately 15 and 6 times higher than their (PM10 and PM2.5) allowable concentrations set by World Health Organization, posing a health threat to the workers and staff of the industries. The lifetime carcinogenic risk of black carbon and the non-carcinogenic risk of particulate matter and black carbon have been assessed using a deterministic and probabilistic model, which shows the marginal difference. The estimated lifetime carcinogenic risk due to black carbon for males and females was observed in the range of 7.20E-05 to 6.17E-05. The spirometry analysis indicates that about 13.04% of the sample population (out of 184 samples) have healthy lungs.

Dynamic anomaly detection in industrial robot clusters: A statistical-deep learning hybrid approach

Dynamic anomaly detection in industrial robot clusters: A statistical-deep learning hybrid approach

Geographical variation, accumulation risk, and risk management of rice heavy metal(loid) contamination in China.

Geographical variation, accumulation risk, and risk management of rice heavy metal(loid) contamination in China.

Greater vulnerability but stronger recovery: The double-edged role of industrial clustering in climate risk scenarios

Greater vulnerability but stronger recovery: The double-edged role of industrial clustering in climate risk scenarios

Enterprise fission path optimization and dynamic capability construction based on the soft actor-critic algorithm

This study aims to explore the enterprise fission path optimization strategy based on the Soft Actor-Critic (SAC) algorithm and analyze its impact on the parent company and the overall operational efficiency. Firstly, the enterprise finance and marketing data provided by the National Bureau of Statistics public dataset are used for data pre-processing. Secondly, a multi-level reward function is designed that covers short-term financial and market indices. Meanwhile, it incorporates long-term indices that measure dynamic capabilities, such as innovation, market agility, and resource integration. Finally, by introducing the reinforcement learning algorithm of SAC, the enterprise fission scenario is constructed into a complicated decision environment, in which the state space includes the current financial situation, market performance, and dynamic capability level of the enterprise. The action space encompasses various strategic choices of enterprise fission to simulate the enterprise fission decision process. The SAC algorithm’s entropy regularization feature prompts the model to strike a balance between exploration and utilization to optimize the dynamic capability construction. The experimental results show that the fission path optimized by deep reinforcement learning (DRL) markedly improves the resource allocation efficiency and market response speed by an average of 20.4% and 25.2%, respectively. More importantly, dynamic capability construction has been significantly enhanced, with the innovation capability index increasing by 15.4%, market agility improving by 12.3%, and resource integration capability also enhancing by 10.5%. This indicates that the strategy can help accelerate the formation of industrial clusters. Therefore, the SAC algorithm-based enterprise fission path optimization strategy constructed in this study can bring lasting competitive advantages to enterprises.

Insight into VOCs source profiles by machine learning: Role of commonalities in synergistic pollution controls.

Insight into VOCs source profiles by machine learning: Role of commonalities in synergistic pollution controls.

Spatial evolution and resilience analysis of marine eco-environmental protection enterprises.

Spatial evolution and resilience analysis of marine eco-environmental protection enterprises.

Decoding the spatiotemporal effects of industrial clusters on carbon emissions in a Chinese river basin

Decoding the spatiotemporal effects of industrial clusters on carbon emissions in a Chinese river basin

Do conflicts in cooperation matter to open innovation? An empirical study of industrial clusters in China

Do conflicts in cooperation matter to open innovation? An empirical study of industrial clusters in China

The impact of pilot policy for innovative industrial clusters on green innovation efficiency

Green transformation has become a central goal of China’s development strategy in response to mounting environmental pressure and long-term growth needs. Improving green innovation efficiency (GIE) is essential to achieving this transformation while sustaining economic momentum. This study evaluates the impact of the Pilot Policy for Innovative Industrial Clusters on GIE across Chinese cities. Using panel data from 280 prefecture-level cities between 2007 and 2021, we apply difference-in-differences and spatial difference-in-differences (SDID) models to estimate policy effects, spatial spillovers, and transmission mechanisms. The results are as follows: (1) The pilot policy significantly improves GIE in the pilot cities, with robust results after various tests. (2) The policy enhances urban green innovation through four main channels: reducing energy consumption intensity, upgrading industrial structure, fostering green technological innovation, and accelerating digital infrastructure development. (3) In addition to its direct impact on pilot cities, the policy also boosts the GIE of neighboring cities via spatial spillover effects. (4) Heterogeneity analysis reveals that the policy’s effect is more pronounced in central cities, non-resource cities, and cities with a strong environmental protection focus. This study contributes to the understanding of innovative industrial cluster policies in enhancing GIE and offers valuable policy insights for promoting urban green development.

Exploring the driving mechanisms behind the formation of agricultural science and technology innovation clusters: a case study of Lanling County, China

This study examines the mechanisms underlying the formation and development of agricultural science and technology innovation clusters, using Lanling County in China as a representative case. It addresses how localized innovation strategies contribute to rural industrial transformation within the broader context of national agricultural modernization. Employing a qualitative case study approach, the research integrates field observations, semi-structured interviews, and document analysis. The analytical framework is informed by industrial cluster theory and the regional innovation systems perspective. The study identifies and examines the interactive dynamics among four major drivers: natural and socioeconomic resource endowments, market demand, policy support, and technological innovation. The findings reveal that the emergence and consolidation of the Lanling vegetable innovation cluster is the outcome of synergetic interactions between endogenous innovation capabilities and exogenous enabling conditions. Strategic interventions—such as the construction of intelligent greenhouses, the expansion of specialized production bases, cooperative organization development, and the implementation of quality control systems—have collectively advanced the region's agricultural upgrading. The study contributes to theoretical discourse by extending cluster theory to the agricultural sector and illustrating the applicability of regional innovation systems in rural contexts. Practically, it offers policy-relevant pathways including the enhancement of technological service networks, market responsiveness, environmental governance, and enterprise collaboration. The research provides replicable insights for other regions seeking to promote sustainable agricultural transformation through innovation-driven development.

LOCAL ECONOMIC DEVELOPMENT STRATEGY THROUGH HUMAN RESOURCE EMPOWERMENT IN THE MSME SECTOR IN MEDAN CITY

This study aims to analyze local economic development strategies through human resource empowerment in the MSME sector in Medan City. The methodology of this research employs a descriptive qualitative approach, collecting data from primary sources by distributing questionnaires to respondents using the pentahelix collaboration model (ABCGM), comprising academics, businesspeople, communities, government, and media. Analysis technique by analyzing the integration of SOAR matrix strategies (Strength, Opportunity, Aspiration, and Result). The results of the analysis show that the MSME development strategy produces four strategies, namely: (1) comprehensive training and mentoring programs for human capital formation, (2) development of the MSME digital ecosystem towards a knowledge-based economy, (3) strengthening the PentaHelix collaboration (ABCGM) as a governance innovation, and (4) developing industrial clusters based on local potential for regional competitive advantage. The study's findings have profound implications for the development of MSME policy at local, regional, and national governance levels. The validated strategic framework provides compelling evidence in support of integrated policy approaches that deliberately transcend traditional sectoral boundaries and administrative silos, arguing for comprehensive policy coordination mechanisms that address MSME development as a complex, interconnected challenge rather than a series of discrete problems. The research highlights the critical importance of developing an institutional framework, suggesting that policy attention should prioritize governance structures and coordination mechanisms over narrowly focused program-specific interventions that fail to address systemic constraints on MSME growth and competitiveness.

Digital platforms and ecosystems as a factor of clusterization and innovative development of regions

Purpose: is to determine the impact of Russian digital platforms and ecosystems on the processes of innovative development and clustering of the economy of Russian regions. Methods: the research is based on the scientific concepts and models within the framework of the theories of cluster development and digital transformation of the economy, in particular, the model of development of territorial innovation clusters. The following methods of statistical research were used: summary and grouping of statistical information, sample observation, correlation analysis. Results: the attributive features of economic ecosystems are highlighted, which include innovation clusters, digital platforms and ecosystems. The theoretical approaches to defining a digital ecosystem are discussed, and the author provides definitions for the following concepts: digital platform, digital ecosystem, digital service, innovation cluster, industrial cluster, and innovative business networks. The features that characterize digital ecosystems are identified, and 12 Russian ecosystems are identified based on these features. Development models are systematized, classification criteria and types of digital platforms are clarified. The current trends in the development of digital platforms and ecosystems are considered, and the level of development of Russian ecosystems is assessed. The analysis of the use of digital platforms and other modern information technologies in Russian regions is carried out, the influence of the use of digital platforms on the processes of innovative development and clustering of subjects of innovative activity at the regional level is considered. Conclusions and Relevance: the development of innovative and hybrid (innovation-transactional) platforms within the Russian digital ecosystems, as well as their integration with innovation clusters, are considered as a factor in the digital transformation of the economy of Russian regions. The author's model of an innovative hypercluster, which is a type of innovation clusters developing on the basis of digital platforms, is proposed as a new organizational form of this integration. The features of the innovative hypercluster model are multi-industry specialization, the trans-regional nature of economic activity and the multicore structure of network interactions of participants.

Research on Security Issues and Countermeasures of Key Software Industry Chain and Supply Chain in China

Currently, the global landscape is undergoing rapid transformation. The trend of economic globalization is experiencing a reversal, unilateralism and protectionism are on the rise, geopolitical conflicts are intensifying, and global industrial and supply chains are undergoing accelerated restructuring. Represented by the United States, Western countries have elevated software supply chain security to a national strategy and introduced a series of policies to strengthen critical software supply chain security. Compared with developed countries in Europe and America, the weak industrial foundation and low level of industrial chain have become the “Achilles heel” that affects the high-quality development of China' s manufacturing industry and even national economic security. Therefore, improving the security level of China' s key software industry chain and supply chain is of great significance for cultivating new quality productivity, promoting new industrialization, and implementing the overall national security concept. From a security perspective, this article combs through the development status and achievements of China' s critical software industry chain and supply chain, deeply deconstructs the potential risks and weak links in such aspects as technological autonomy, ecological construction, and risk prevention and control, and puts forward suggestions from the dimensions of strategic layout, technological breakthrough, system construction, industrial cluster, etc. , so as to provide support for building a security governance system for China' s critical software industry chain and supply chain.